The Langat River water quality index based on principal component analysis | Zendy

Zalina Mohd Ali | Zendy; Noor Akma Ibrahim | Zendy; Kerrie Mengersen | Zendy; Mahendran Shitan | Zendy; Hafizan Juahir | Zendy

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The Langat River water quality index based on principal component analysis

Author(s) -

Zalina Mohd Ali,

Noor Akma Ibrahim,

Kerrie Mengersen,

Mahendran Shitan,

Hafizan Juahir

Publication year - 2013

Publication title -

aip conference proceedings

Language(s) - English

Resource type - Conference proceedings

SCImago Journal Rank - 0.177

H-Index - 75

eISSN - 1551-7616

pISSN - 0094-243X

DOI - 10.1063/1.4801283

Subject(s) - principal component analysis , water quality , ranking (information retrieval) , biochemical oxygen demand , index (typography) , multivariate statistics , ammoniacal nitrogen , total dissolved solids , curse of dimensionality , quality (philosophy) , chemical oxygen demand , statistics , environmental science , mathematics , hydrology (agriculture) , environmental engineering , computer science , artificial intelligence , ecology , philosophy , geotechnical engineering , epistemology , wastewater , world wide web , engineering , biology

River Water Quality Index (WQI) is calculated using an aggregation function of the six water quality sub-indices variables, together with their relative importance or weights respectively. The formula is used by the Department of Environment to indicate a general status of the rivers in Malaysia. The six elected water quality variables used in the formula are, namely: suspended solids (SS), biochemical oxygen demand (BOD), ammoniacal nitrogen (AN), chemical oxygen demand (COD), dissolved oxygen (DO) and pH. The sub-indices calculations, determined by quality rating curve and their weights, were based on expert opinions. However, the use of sub-indices and the relative importance established in the formula is very subjective in nature and does not consider the inter-relationships among the variables. The relationships of the variables are important due to the nature of multi-dimensionality and complex characteristics found in river water. Therefore, a well-known multivariate technique, i.e. Principal Compo...

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